This pipeline was finetuned from runwayml/stable-diffusion-v1-5 on the lylz/dataset_hw4_cleaned dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['月上柳梢头，人约黄昏后。']:

Pipeline usage

You can use the pipeline like so:

python

from diffusers import DiffusionPipeline
import torch

pipeline = DiffusionPipeline.from_pretrained("lylz/poem-sd-full", torch_dtype=torch.float16)
prompt = "月上柳梢头，人约黄昏后。"
image = pipeline(prompt).images[0]
image.save("my_image.png")

Training info

These are the key hyperparameters used during training:

Epochs: 10
Learning rate: 1e-05
Batch size: 16
Gradient accumulation steps: 1
Image resolution: 512
Mixed-precision: fp16

Intended uses & limitations

How to use

# TODO: add an example code snippet for running this diffusion pipeline

Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

Training details

[TODO: describe the data used to train the model]